In this work we focus on stacked and deep transition recurrent architectures as defined by [1]}.
Different types of stacked architectures have been successfully used for NMT [2]}, [3]}.
However, there is a lack of empirical comparisons of different deep architectures.
Deep transition architectures have been successfully used for language modeling [4]}, but not for NMT so far.
We evaluate these architectures, both alone and in combination, varying the connection scheme between the different components and their depth over the different dimensions, measuring the performance of the different configurations on the WMT news translation task.http://www.statmt.org/wmt17/translation-task.html
